The large amount of data used on web resources contributes to their slowdown, which negatively affects the loading time and the overall impression of the work. Caching servers, which temporarily store frequently requested data closer to the user, can significantly reduce the response time of servers, reduce the load on the primary computing resources, and increase the stability of web applications. Their implementation becomes especially relevant in the case of highly loaded web services. Modern web pages often take a long time to load due to a combination of technical factors, such as the volume of data and server load. In this work, the architecture of the server part of the web resource for processing big data with high load elements has been developed to speed up the work of web resources. A load balancer and caching servers have been chosen to speed up the work. One of the key factors determining the speed of modern web resources is the effective use of caching mechanisms. Caching servers allow you to store intermediate calculation results, static files, and pre-generated pages, which significantly reduces the system's response time to repeated requests. The lack of a cache means that each request is processed “from scratch,” even if the data hasn’t changed. This increases the risk of overload, especially during peak traffic or DDoS-like spikes in activity. Powerful computing nodes waste resources regenerating the same responses, which increases infrastructure costs. Effective caching often requires separate servers or cloud services like Redis, Varnish, CDN. This increases hardware costs or the need to rent additional resources from cloud providers. The balancer prevents overloading of individual servers by distributing requests between them. This ensures stable operation even during peak hours of user activity and reduces the risk of failures. In the event of a server failure, the balancer can automatically redirect traffic to other working nodes. This reduces the likelihood of complete system downtime and increases service availability. The proposed architecture is adapted to the development of web resources with elements of Unet networks, which are characterized by the presence of a large amount of static content. Comparative analysis demonstrates that web page loading time decreased by an average of 3 times using caching servers.
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